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A Framework for Arabic Tweets Multi-label Classification Using Word Embedding and Neural Networks Algorithms

Authors:

Abdullah M. Bdeir,

Farid IbrahimAuthors Info & Claims

BDE '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering

Pages 105 - 112

https://doi.org/10.1145/3404512.3404526

Published: 05 July 2020 Publication History

Abstract

The need for classifying tweets is essential for many people like tourists, tourism companies and governments. In this paper, we propose a framework for Arabic Tweets multi-label classification using word embedding technique and deep leering algorithms. We built our dataset using 160k Arabic tweets gathered from Twitter. We compared two deep learning methods, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). Our results show that it is possible to classify tweets using our methodology without any significant difference in results of accuracy scores and hamming loss for both types of networks. The accuracy scores and hamming loss were nearly 90% and 0.02, respectively.

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Cited By

Alshammary HIbrahim MHussein H(2024)Evaluating The Impact of Feature Extraction Techniques on Arabic Reviews ClassificationInfoTech Spectrum: Iraqi Journal of Data Science10.51173/ijds.v1i1.10(42-54)Online publication date: 1-Jun-2024
https://doi.org/10.51173/ijds.v1i1.10
Lin CThanoon MKarali S(2024)A Deep Learning-based Classification Model for Arabic News Tweets Using Bidirectional Long Short-Term Memory NetworksPertanika Journal of Science and Technology10.47836/pjst.32.4.0932:4(1609-1628)Online publication date: 16-Jul-2024
https://doi.org/10.47836/pjst.32.4.09
Salem AMedhat WGamalElDin N(2024)Exploring State-of-the-Art Models in Arabic NLP: Insights into Multi-Label Text Classification2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES)10.1109/NILES63360.2024.10753176(533-538)Online publication date: 19-Oct-2024
https://doi.org/10.1109/NILES63360.2024.10753176
Show More Cited By

Index Terms

A Framework for Arabic Tweets Multi-label Classification Using Word Embedding and Neural Networks Algorithms
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction

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BDE '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering

May 2020

146 pages

ISBN:9781450377225

DOI:10.1145/3404512

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 05 July 2020

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BDE 2020

BDE 2020: 2020 2nd International Conference on Big Data Engineering

May 29 - 31, 2020

Shanghai, China

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Cited By

Alshammary HIbrahim MHussein H(2024)Evaluating The Impact of Feature Extraction Techniques on Arabic Reviews ClassificationInfoTech Spectrum: Iraqi Journal of Data Science10.51173/ijds.v1i1.10(42-54)Online publication date: 1-Jun-2024
https://doi.org/10.51173/ijds.v1i1.10
Lin CThanoon MKarali S(2024)A Deep Learning-based Classification Model for Arabic News Tweets Using Bidirectional Long Short-Term Memory NetworksPertanika Journal of Science and Technology10.47836/pjst.32.4.0932:4(1609-1628)Online publication date: 16-Jul-2024
https://doi.org/10.47836/pjst.32.4.09
Salem AMedhat WGamalElDin N(2024)Exploring State-of-the-Art Models in Arabic NLP: Insights into Multi-Label Text Classification2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES)10.1109/NILES63360.2024.10753176(533-538)Online publication date: 19-Oct-2024
https://doi.org/10.1109/NILES63360.2024.10753176
Al-Smadi B(2024)DeBERTa-BiLSTM: A multi-label classification model of Arabic medical questions using pre-trained models and deep learningComputers in Biology and Medicine10.1016/j.compbiomed.2024.107921170(107921)Online publication date: Mar-2024
https://doi.org/10.1016/j.compbiomed.2024.107921
Al-Jarrah IMustafa ANajadat H(2023)Aspect-Based Sentiment Analysis for Arabic Food Delivery ReviewsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/360514622:7(1-18)Online publication date: 20-Jul-2023
https://dl.acm.org/doi/10.1145/3605146
Bahurmuz NAmoudi GBaothman FJamal AAlghamdi HAlhothali A(2022)Arabic Rumor Detection Using Contextual Deep Bidirectional Language ModelingIEEE Access10.1109/ACCESS.2022.321752210(114907-114918)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3217522
Al-Ayyoub MSeelawi HZaghlol MAl-Natsheh HSuileman SFadel ABadawi RMorsy ATuffaha IAljarrah M(2021)Overview of the Mowjaz Multi-Topic Labelling Task2021 12th International Conference on Information and Communication Systems (ICICS)10.1109/ICICS52457.2021.9464604(502-508)Online publication date: 24-May-2021
https://doi.org/10.1109/ICICS52457.2021.9464604
Ghourabi A(2021)A BERT-based system for multi-topic labeling of Arabic content2021 12th International Conference on Information and Communication Systems (ICICS)10.1109/ICICS52457.2021.9464540(486-489)Online publication date: 24-May-2021
https://doi.org/10.1109/ICICS52457.2021.9464540

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